The present invention relates generally to statistical analysis computer systems. More particularly, the present invention relates to statistical impact analysis computer systems.
The desire to improve quality has spread to nearly all manufacturing and service industries, business and social organizations and government. Today there is great interest in improving quality of products, services and the environment through systematic performance evaluation followed by business process improvement. Some (but admittedly few) industries are fortunate to have easily quantifiable metrics to measure the quality of their products and services. Using these metrics a continuous improvement process can be implemented, whereby (a) the product or service is produced using existing processes and assessed using quantifiable metrics, (b) the existing processes are then changed based on the results of the metrics, and (c) the efficacy of the change is tested by producing the product or service again using the changed process and assessing using the same metrics.
For most industries, however, finding a good, quantifiable metric has proven quite elusive. For most industries, business processes have become quite complex and quite hard to describe in quantitative terms. Human intuition and judgment play an important role in production of goods and services; and ultimately human satisfaction plays the decisive role in determining which goods and services sell well and which do not. In addition, there is a growing body of evidence suggesting that employee on-the-job satisfaction also has an enormous impact upon a company's bottom line.
Human intuition and judgment, customer satisfaction, employee satisfaction. These are intangible variables that are not directly measurable and must therefore be inferred from data that are measurable. Therein lies the root of a major problem in applying continuous improvement techniques to achieve better quality. The data needed to improve quality are hidden, often deeply within reams of data the organization generates for other purposes. Even surveys expressly designed to uncover this hidden data can frequently fail to produce meaningful results unless the data are well understood and closely monitored.
Experts in statistical analysis know to represent such intangible variables as "latent variables" that are derived from measurable variables, known as "manifest variables." However, even experts in statistical analysis cannot say that manifest variable A will always measure latent variable B. The relationship is rarely that direct. More frequently, the relationship between manifest variable A and latent variable B involves a hypothesis, which must be carefully tested through significant statistical analysis before being relied upon.
The current state of the art is to analyze these hypotheses on a piecemeal basis, using statistical analysis packages such as SPSS or SAS. However, these packages are not designed or intended for the casual user. These packages lack a semi-automated (let alone an automated mechanism) for examining the "manifest" variables (i.e., measured survey data) within many different cuts or segments. Also, these packages have difficulty dealing with surveys where the data are incomplete or few responses have been gathered.
Moreover, these packages lack a cohesive semi-automated mechanism for determining the impact of these measured manifest variables upon "latent" variables (such as customer satisfaction) which cannot be directly measured due to their intangible nature.
The present invention is directed to overcoming these and other disadvantages of previous systems. In accordance with the teachings of the present invention, a computer-implemented apparatus and method is provided for determining the impacts of predetermined customer characteristics associated with measured physical attributes. A manifest variable database is utilized for storing manifest variable data that is indicative of the measured physical attributes. A partial least squares determinator is connected to the manifest variable database for determining statistical weights based upon the stored manifest variable data. A weights database which is connected to the partial lease squares determinator is utilized for storing the determined weights.
A latent variable determinator is connected to the weighting database for determining scores for latent variables based upon the stored manifest variables and upon the stored weights. The latent variables are indicative of the predetermined customer characteristics. Additionally, a latent variable database is connected to the latent variable score determinator for storing the determined latent variable scores. An impact determinator is connected to the latent variable database for determining impact relationships among the latent variables based upon the stored latent variable scores.
For a more complete understanding of the invention, its objects and advantages, reference may be had to the following specification and to the accompanying drawings.